Driver drowsiness detection

Registration ID: IJNRD_217906

Published ID: IJNRD2404305

DOI: Click Here to Get

K.Nandini , M.chandana , G. Vandana sai , G.Lavanya , R. Snehanjali

Drowsiness Detection; facial expression; Machine learning; behavioral measures.

This paper presents a literature review of driver drowsiness detection based on behavioral measures using machine learning techniques. Faces contain information that can be used to interpret levels of drowsiness. There are many facial features that can be extracted from the face to infer the level of drowsiness. These include eye blinks, head movements and yawning. However, the development of a drowsiness detection system that yields reliable and accurate results is a challenging task as it requires accurate and robust algorithms. A wide range of techniques has been examined to detect driver drowsiness in the past. The recent rise of deep learning requires that these algorithms be revisited to evaluate their accuracy in detection of drowsiness. As a result, this paper reviews machine learning techniques which include support vector machines, convolutional neural networks and hidden Markov models in the context of drowsiness detection. Furthermore, a meta-analysis is conducted on 25 papers that use machine learning techniques for drowsiness detection. The analysis reveals that support vector machine technique is the most commonly used technique to detect drowsiness, but convolutional neural networks performed better than the other two techniques. Finally, this paper lists publicly available datasets that can be used as benchmarks for drowsiness detection.

Published Paper   E-Certificate

K.Nandini, M.chandana, G. Vandana sai, G.Lavanya, & R. Snehanjali (April-2024). Driver drowsiness detection. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), d32-d40. https://ijnrd.org/papers/IJNRD2404305.pdf

Volume 9 Issue 4, April-2024

Pages : d32-d40

Paper Reg. ID: IJNRD_217906

Published Paper Id: IJNRD2404305

Downloads: 000121982

Research Area: Computer Engineering 

Country: Anantapur, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404305.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404305

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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